Research on data storage and index of EMMDB

This paper proposes the EHAS and the PMCT-tree algorithms as more efficient ones on data organization and index of Embedded Main-Memory Database (EMMDB). Based on area-segment method, the EHAS is a storage algorithm combined with quasi-extendible hashing. It locates and stores records with corresponding unique triples, each of which consists of an area sign, a segment sign and a storage address sign. Compared with the traditional T-tree, a Priority Match Catalog (PMC) is added to the PMCT-tree. And the PMC is mainly composed of some edges thresholds, which are extracted from T-tree nodes. Experimental results have indicated that the EHAS algorithm accelerates storage response time and its average querying time complexity can reach a constant level under certain conditions. Besides, the PMCT-tree algorithm is efficient and effective in querying response time.